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Kata Containers and service mesh for Kubernetes

A service mesh is a way to monitor and control the traffic between micro-services running in your Kubernetes cluster. It is a powerful tool that you might want to use in combination with the security brought by Kata Containers.

Assumptions

You are expected to be familiar with concepts such as pods, containers, control plane, data plane, and sidecar.

How they work

Istio and Linkerd both rely on the same model, where they run controller applications in the control plane, and inject a proxy as a sidecar inside the pod running the service. The proxy registers in the control plane as a first step, and it constantly sends different sorts of information about the service running inside the pod. That information comes from the filtering performed when receiving all the traffic initially intended for the service. That is how the interaction between the control plane and the proxy allows the user to apply load balancing and authentication rules to the incoming and outgoing traffic, inside the cluster, and between multiple micro-services.

This cannot not happen without a good amount of iptables rules ensuring the packets reach the proxy instead of the expected service. Rules are setup through an init container because they have to be there as soon as the proxy starts.

Prerequisites

Kata and Kubernetes

Follow the instructions to get Kata Containers properly installed and configured with Kubernetes. You can choose between CRI-O and containerd, both are supported through this document.

For both cases, select the workloads as trusted by default. This way, your cluster and your service mesh run with runc, and only the containers you choose to annotate run with Kata Containers.

Restrictions

As documented here, a kernel version between 4.14.22 and 4.14.40 causes a deadlock when getsockopt() gets called with the SO_ORIGINAL_DST option. Unfortunately, both service meshes use this system call with this same option from the proxy container running inside the VM. This means that you cannot run this kernel version range as the guest kernel for Kata if you want your service mesh to work.

As mentioned when explaining the basic functioning of those service meshes, iptables are heavily used, and they need to be properly enabled through the guest kernel config. If they are not properly enabled, the init container is not able to perform a proper setup of the rules.

Install and deploy your service mesh

Service Mesh Istio

The following is a summary of what you need to install Istio on your system:

$ curl -L https://git.io/getLatestIstio | sh -
$ cd istio-*
$ export PATH=$PWD/bin:$PATH

See the Istio documentation for further details.

Now deploy Istio in the control plane of your cluster with the following:

$ kubectl apply -f install/kubernetes/istio-demo.yaml

To verify that the control plane is properly deployed, you can use both of the following commands:

$ kubectl get svc -n istio-system
$ kubectl get pods -n istio-system -o wide

Service Mesh Linkerd

As a reference, follow the Linkerd instructions.

The following is a summary of what you need to install Linkerd on your system:

$ curl https://run.linkerd.io/install | sh
$ export PATH=$PATH:$HOME/.linkerd/bin

Now deploy Linkerd in the control plane of your cluster with the following:

$ linkerd install | kubectl apply -f -

To verify that the control plane is properly deployed, you can use both of the following commands:

$ kubectl get svc -n linkerd
$ kubectl get pods -n linkerd -o wide

Inject your services with sidecars

Once the control plane is running, you need a deployment to define a few services that rely on each other. Then, you inject the YAML file with the sidecar proxy using the tools provided by each service mesh.

If you do not have such a deployment ready, refer to the samples provided by each project.

Sidecar Istio

Istio provides a bookinfo sample, which you can rely on to inject their envoy proxy as a sidecar.

You need to use their tool called istioctl kube-inject to inject your YAML file. We use their bookinfo sample as an example:

$ istioctl kube-inject -f samples/bookinfo/kube/bookinfo.yaml -o bookinfo-injected.yaml

Sidecar Linkerd

Linkerd provides an emojivoto sample, which you can rely on to inject their linkerd proxy as a sidecar.

You need to use their tool called linkerd inject to inject your YAML file. We use their emojivoto sample as example:

$ wget https://raw.githubusercontent.com/runconduit/conduit-examples/master/emojivoto/emojivoto.yml
$ linkerd inject emojivoto.yml > emojivoto-injected.yaml

Run your services with Kata

Now that your service deployment is injected with the appropriate sidecar containers, manually edit your deployment to make it work with Kata.

Lower privileges

In Kubernetes, the init container is often privileged as it needs to setup the environment, which often needs some root privileges. In the case of those services meshes, all they need is the NET_ADMIN capability to modify the underlying network rules. Linkerd, by default, does not use privileged container, but Istio does.

Because of the previous reason, if you use Istio you need to switch all containers with privileged: true to privileged: false.

Add annotations

There is no difference between Istio and Linkerd in this section. It is about which CRI implementation you use.

For both CRI-O and containerd, you have to add an annotation indicating the workload for this deployment is not trusted, which will trigger kata-runtime to be called instead of runc.

CRI-O:

Add the following annotation for CRI-O

io.kubernetes.cri-o.TrustedSandbox: "false"

The following is an example of what your YAML can look like:

...
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  creationTimestamp: null
  name: details-v1
spec:
  replicas: 1
  strategy: {}
  template:
    metadata:
      annotations:
        io.kubernetes.cri-o.TrustedSandbox: "false"
        sidecar.istio.io/status: '{"version":"55c9e544b52e1d4e45d18a58d0b34ba4b72531e45fb6d1572c77191422556ffc","initContainers":["istio-init"],"containers":["istio-proxy"],"volumes":["istio-envoy","istio-certs"],"imagePullSecrets":null}'
      creationTimestamp: null
      labels:
        app: details
        version: v1
...

containerd:

Add the following annotation for containerd

io.kubernetes.cri.untrusted-workload: "true"

The following is an example of what your YAML can look like:

...
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  creationTimestamp: null
  name: details-v1
spec:
  replicas: 1
  strategy: {}
  template:
    metadata:
      annotations:
        io.kubernetes.cri.untrusted-workload: "true"
        sidecar.istio.io/status: '{"version":"55c9e544b52e1d4e45d18a58d0b34ba4b72531e45fb6d1572c77191422556ffc","initContainers":["istio-init"],"containers":["istio-proxy"],"volumes":["istio-envoy","istio-certs"],"imagePullSecrets":null}'
      creationTimestamp: null
      labels:
        app: details
        version: v1
...

Deploy

Deploy your application by using the following:

$ kubectl apply -f myapp-injected.yaml